An increasing variety of industrial applications involve machine vision measurements taken by processing image data from cameras. For example, wheels of motor vehicles may be aligned on an alignment rack using a computer-aided, three-dimensional (3D) machine vision alignment apparatus. In such a technique, one or more cameras of the alignment apparatus view targets attached to the wheels of the vehicle. The cameras form images of the targets, and a computer in the alignment apparatus analyzes the images of the targets to determine wheel position. The computer guides an operator in properly adjusting the wheels to accomplish precise alignment, based on calculations obtained from processing of the image data.
Examples of methods and apparatus useful in 3D alignment of motor vehicles are described in U.S. Pat. No. 5,943,783 entitled “Method and apparatus for determining the alignment of motor vehicle wheels;” U.S. Pat. No. 5,809,658 entitled “Method and apparatus for calibrating cameras used in the alignment of motor vehicle wheels;” U.S. Pat. No. 5,724,743 entitled “Method and apparatus for determining the alignment of motor vehicle wheels;” and U.S. Pat. No. 5,535,522 entitled “Method and apparatus for determining the alignment of motor vehicle wheels.”
A wheel alignment system of the type described in these references is sometimes called a “3D aligner” or “aligner.” An example of a commercial vehicle wheel aligner is the Visualiner 3D, commercially available from John Bean Company, Conway, Ark., a unit of Snap-on Tools Company. Of course, the 3D wheel aligner discussed above is described here as just one example of a system utilizing machine vision in a commercial application.
In a 3D aligner and in other applications involving machine vision, there is a substantial amount of processing required to interpret camera images. In current machine vision systems, such as the 3D aligners, there are two general ways to process the video image signals from the cameras, both of which have limitations or problems.
The most common image processing technique in industrial machine vision applications utilizes a dedicated video processing module, comprising hard-wired and other processing devices specifically designed and adapted to process the image data before input of processed results to the host computer. In alignment systems, for example, such a board processes signals from one or more cameras to produce target orientation results or possibly even alignment numbers, for display and/or further processing by the host computer. However, video processing boards often require use of complex, expensive processors to perform all of the necessary calculations required for the image algorithms.
The alternative approach to processing image data for machine vision applications involves streaming image data from the camera(s) to an image capture board whose image memory is accessible by the host computer. The host computer, in turn, performs all of the processing of the image data, which would otherwise be done on the dedicated video processing module, to obtain the necessary calculation results. However, the amount of processing required is quite large and imposes a substantial burden on the central processing unit of the host computer. Such intense processing may unacceptably slow down operation of the host computer. If the particular machine vision application requires processing of images from multiple cameras, the amount of the data to be handled and the attendant number of necessary calculations may overwhelm the host computer.